measuring each of the first chords D1 to obtain a plurality of first dimensions;computing for each of the first chords D1 a second chord D2 across the periphery thus forming a plurality of D1, D2 pairs of chords;measuring the second chords D2 for all pairs to obtain second dimensions;computing for each of the pairs of first chords D1 and second chords D2 the ratio D1/D2 of the first dimension to the second dimension to obtain a plurality of first values;computing the logarithm of the first values to obtain a plurality of logarithmic values;computing difference values by subtracting the second dimension from the first dimension for each of the pairs;recording the first values, logarithmic values and difference values in histograms;extracting a vertex lists from the histograms;combining one or more of the vertex lists to obtain a signature indicative of the classification of the object target.;For each of the pairs, the second chords are orthogonal to the first chords, and the second chords share a point with the first chords and the periphery."/> Recognition algorithm for the unknown target rejection based on shape statistics obtained from orthogonal distance function
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Recognition algorithm for the unknown target rejection based on shape statistics obtained from orthogonal distance function

机译:基于正交距离函数得到的形状统计信息的未知目标剔除识别算法

摘要

A method for classification of a target object having a periphery comprises the steps of: selecting a plurality of random first chords D1 across the periphery of the target object;measuring each of the first chords D1 to obtain a plurality of first dimensions;computing for each of the first chords D1 a second chord D2 across the periphery thus forming a plurality of D1, D2 pairs of chords;measuring the second chords D2 for all pairs to obtain second dimensions;computing for each of the pairs of first chords D1 and second chords D2 the ratio D1/D2 of the first dimension to the second dimension to obtain a plurality of first values;computing the logarithm of the first values to obtain a plurality of logarithmic values;computing difference values by subtracting the second dimension from the first dimension for each of the pairs;recording the first values, logarithmic values and difference values in histograms;extracting a vertex lists from the histograms;combining one or more of the vertex lists to obtain a signature indicative of the classification of the object target.;For each of the pairs, the second chords are orthogonal to the first chords, and the second chords share a point with the first chords and the periphery.
机译:一种具有周边的目标物体的分类方法,包括以下步骤:在目标物体的周边上选择多个随机的第一和弦D 1 ; 测量每个第一和弦D 1 以获得多个第一维度; 计算每个第一和弦D 1 和第二和弦D 2 沿整个圆周形成多个D 1 ,D 2 < / B>对和弦; 测量所有对的第二和弦D 2 以获得第二维; 为第一对和弦D 1 和第二对和弦D 2 中的每对计算比率D <从第一维度的B> 1 / D 2 到第二维度,以获得多个第一值; 计算第一值的对数以获得多个对数; 通过从每个对的第一维中减去第二维来计算差异值; 在直方图中记录第一个值,对数值和差值; 从直方图中提取顶点列表; 组合一个或多个顶点列表以获得表示对象目标分类的签名。 ;对于每对,第二和弦与第一和弦正交,并且第二和弦与第一和弦和外围共享一个点。

著录项

  • 公开/公告号US7116265B2

    专利类型

  • 公开/公告日2006-10-03

    原文格式PDF

  • 申请/专利权人 DAVID B. SHU;CYNTHIA E. DANIELL;

    申请/专利号US20050054757

  • 发明设计人 DAVID B. SHU;CYNTHIA E. DANIELL;

    申请日2005-02-10

  • 分类号G01S13/90;

  • 国家 US

  • 入库时间 2022-08-21 21:42:35

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